Exploration
Seraphina Shi
Load Data from the Clock Calculator
1. Table with summarize info [table 1]
1.1. Description of study population (all visits)
Baseline characteristics (confounders)
| Overall (N=129) |
|
|---|---|
| Age | |
| Mean (SD) | 57.6 (14.5) |
| Median (IQR) | 60.0 (23.0) |
| BMI | |
| Mean (SD) | 22.0 (3.47) |
| Median (IQR) | 21.8 (3.92) |
| factor(county) | |
| Fuyuan | 63 (48.8%) |
| Xuanwe | 66 (51.2%) |
| factor(ses) | |
| 0 | 71 (55.0%) |
| 1 | 58 (45.0%) |
| factor(edu) | |
| 1 | 90 (69.8%) |
| 2 | 20 (15.5%) |
| 3 | 14 (10.9%) |
| 4 | 5 (3.9%) |
Epigenetic ages
| Overall (N=129) |
|
|---|---|
| DNAmAge | |
| Mean (SD) | 57.6 (13.1) |
| Median (IQR) | 59.4 (21.0) |
| DNAmAgeHannum | |
| Mean (SD) | 60.4 (13.9) |
| Median (IQR) | 61.8 (22.8) |
| DNAmPhenoAge | |
| Mean (SD) | 56.2 (13.5) |
| Median (IQR) | 58.0 (20.5) |
| DNAmAgeSkinBloodClock | |
| Mean (SD) | 57.1 (12.7) |
| Median (IQR) | 59.8 (20.9) |
| DNAmGrimAge | |
| Mean (SD) | 56.2 (11.3) |
| Median (IQR) | 57.6 (17.7) |
| DNAmTL | |
| Mean (SD) | 6.82 (0.321) |
| Median (IQR) | 6.82 (0.452) |
Epigenetic ages accelarations
| Overall (N=129) |
|
|---|---|
| AgeAccelerationResidual | |
| Mean (SD) | 0.359 (4.63) |
| Median (IQR) | 0.140 (5.83) |
| AgeAccelerationResidualHannum | |
| Mean (SD) | -0.235 (4.01) |
| Median (IQR) | -0.376 (4.64) |
| AgeAccelPheno | |
| Mean (SD) | -0.397 (4.28) |
| Median (IQR) | -0.732 (5.28) |
| DNAmAgeSkinBloodClockAdjAge | |
| Mean (SD) | 0.170 (3.41) |
| Median (IQR) | 0.435 (3.59) |
| AgeAccelGrim | |
| Mean (SD) | -0.440 (2.94) |
| Median (IQR) | -0.659 (3.20) |
| DNAmTLAdjAge | |
| Mean (SD) | 0.0277 (0.180) |
| Median (IQR) | 0.0305 (0.234) |
| IEAA | |
| Mean (SD) | 0.179 (4.24) |
| Median (IQR) | 0.136 (5.56) |
| EEAA | |
| Mean (SD) | -0.296 (5.11) |
| Median (IQR) | -0.174 (6.56) |
Fuel/stove type exposures
| Overall (N=129) |
|
|---|---|
| factor(curFuel) | |
| Smokeles | 18 (14.0%) |
| Smoky | 98 (76.0%) |
| Wood_and_or_Plant | 13 (10.1%) |
| factor(brthFuel) | |
| Mix | 54 (41.9%) |
| Outside of XW/FY | 3 (2.3%) |
| Smokeles | 7 (5.4%) |
| Smoky | 52 (40.3%) |
| Wood | 13 (10.1%) |
| factor(childFuel) | |
| Mix | 63 (48.8%) |
| Smokeles | 5 (3.9%) |
| Smoky | 50 (38.8%) |
| Wood | 11 (8.5%) |
| factor(curFuel_detail) | |
| Plant | 4 (3.1%) |
| Smokeles | 18 (14.0%) |
| Smoky | 98 (76.0%) |
| Wood | 9 (7.0%) |
| factor(cumFuel) | |
| Mix | 84 (65.1%) |
| Smokeles | 1 (0.8%) |
| Smoky | 42 (32.6%) |
| Wood | 2 (1.6%) |
| factor(curStove) | |
| Firepit_and_unventilated | 22 (17.1%) |
| Mix | 19 (14.7%) |
| Portable_stove | 20 (15.5%) |
| Ventilated | 51 (39.5%) |
| Missing | 17 (13.2%) |
5MC exposures
| Overall (N=129) |
|
|---|---|
| cur_5mc | |
| Mean (SD) | 8.15 (4.23) |
| Median (IQR) | 8.26 (4.48) |
| Missing | 3 (2.3%) |
| cum_5mc | |
| Mean (SD) | 275 (150) |
| Median (IQR) | 257 (209) |
| Missing | 3 (2.3%) |
| bir_5mc | |
| Mean (SD) | 5.22 (2.82) |
| Median (IQR) | 4.75 (5.34) |
| Missing | 3 (2.3%) |
| cur_5mc_measured | |
| Mean (SD) | 12.8 (38.1) |
| Median (IQR) | 5.52 (6.17) |
| Missing | 78 (60.5%) |
## [1] "Pearson pair-wise correlation:"## cur_5mc cum_5mc bir_5mc cur_5mc_measured
## cur_5mc 1.0000000 0.7025515 0.63724241 0.13319188
## cum_5mc 0.7025515 1.0000000 0.81021435 0.18607788
## bir_5mc 0.6372424 0.8102143 1.00000000 -0.03066466
## cur_5mc_measured 0.1331919 0.1860779 -0.03066466 1.00000000## [1] "Spearman pair-wise correlation:"## cur_5mc cum_5mc bir_5mc cur_5mc_measured
## cur_5mc 1.0000000 0.6487685 0.5771252 0.4692482
## cum_5mc 0.6487685 1.0000000 0.7918033 0.3290434
## bir_5mc 0.5771252 0.7918033 1.0000000 0.2804710
## cur_5mc_measured 0.4692482 0.3290434 0.2804710 1.0000000Cluster-based exposures
clusCUR6
Clusters based on model-based exposure estimates at or shortly before the visit
| Overall (N=129) |
|
|---|---|
| CUR6_BC_PAH6 | |
| Mean (SD) | 0.194 (1.00) |
| Median (IQR) | 0.799 (1.36) |
| Missing | 3 (2.3%) |
| CUR6_PAH31 | |
| Mean (SD) | 0.192 (1.00) |
| Median (IQR) | 0.437 (1.09) |
| Missing | 3 (2.3%) |
| CUR6_NkF | |
| Mean (SD) | -0.0817 (1.00) |
| Median (IQR) | -0.302 (1.20) |
| Missing | 3 (2.3%) |
| CUR6_PM_RET | |
| Mean (SD) | -0.0374 (1.00) |
| Median (IQR) | -0.316 (0.929) |
| Missing | 3 (2.3%) |
| CUR6_NO2 | |
| Mean (SD) | 0.123 (1.00) |
| Median (IQR) | 0.0189 (1.22) |
| Missing | 3 (2.3%) |
| CUR6_SO2 | |
| Mean (SD) | -0.152 (1.00) |
| Median (IQR) | -0.335 (1.16) |
| Missing | 3 (2.3%) |
clusCHLD5
Clusters based on model-based exposure estimates accrued before age 18
| Overall (N=129) |
|
|---|---|
| CHLD5_X7 | |
| Mean (SD) | -0.0382 (1.00) |
| Median (IQR) | 0.111 (1.10) |
| Missing | 3 (2.3%) |
| CHLD5_X33 | |
| Mean (SD) | 0.155 (1.00) |
| Median (IQR) | 0.00445 (1.67) |
| Missing | 3 (2.3%) |
| CHLD5_NkF | |
| Mean (SD) | -0.0978 (1.00) |
| Median (IQR) | -0.220 (1.34) |
| Missing | 3 (2.3%) |
| CHLD5_NO2 | |
| Mean (SD) | 0.167 (1.00) |
| Median (IQR) | 0.196 (1.16) |
| Missing | 3 (2.3%) |
| CHLD5_SO2 | |
| Mean (SD) | 0.00157 (1.00) |
| Median (IQR) | 0.362 (1.55) |
| Missing | 3 (2.3%) |
clusCUM6
Clusters based on model-based lifetime exposure estimates
| Overall (N=129) |
|
|---|---|
| CUM6_BC_NO2_PM | |
| Mean (SD) | 0.114 (1.00) |
| Median (IQR) | 0.281 (1.44) |
| Missing | 3 (2.3%) |
| CUM6_PAH36 | |
| Mean (SD) | 0.199 (1.00) |
| Median (IQR) | 0.254 (1.77) |
| Missing | 3 (2.3%) |
| CUM6_DlP | |
| Mean (SD) | -0.175 (1.00) |
| Median (IQR) | -0.459 (1.71) |
| Missing | 3 (2.3%) |
| CUM6_NkF | |
| Mean (SD) | -0.0183 (1.00) |
| Median (IQR) | -0.0813 (1.10) |
| Missing | 3 (2.3%) |
| CUM6_RET | |
| Mean (SD) | -0.125 (1.00) |
| Median (IQR) | -0.215 (1.11) |
| Missing | 3 (2.3%) |
| CUM6_SO2 | |
| Mean (SD) | -0.0834 (1.00) |
| Median (IQR) | 0.0951 (1.20) |
| Missing | 3 (2.3%) |
clusMEAS6
Clusters based on pollutant measurements
| Overall (N=129) |
|
|---|---|
| MEAS6_BC_PM_RET | |
| Mean (SD) | -0.0486 (1.00) |
| Median [Min, Max] | -0.104 [-2.12, 2.58] |
| Missing | 64 (49.6%) |
| MEAS6_X31 | |
| Mean (SD) | -0.00352 (1.00) |
| Median [Min, Max] | 0.125 [-1.94, 2.13] |
| Missing | 64 (49.6%) |
| MEAS6_X5 | |
| Mean (SD) | 0.0136 (1.00) |
| Median [Min, Max] | -0.102 [-1.42, 1.75] |
| Missing | 64 (49.6%) |
| MEAS6_DlP | |
| Mean (SD) | 0.0186 (1.00) |
| Median [Min, Max] | -0.627 [-1.02, 1.76] |
| Missing | 64 (49.6%) |
| MEAS6_NkF | |
| Mean (SD) | 0.00902 (1.00) |
| Median [Min, Max] | -0.489 [-1.18, 1.85] |
| Missing | 64 (49.6%) |
| MEAS6_NO2_SO2 | |
| Mean (SD) | 0.0902 (1.00) |
| Median [Min, Max] | -0.0368 [-1.56, 2.06] |
| Missing | 64 (49.6%) |
clusURI5
Clusters based on urinary biomarkers
| Overall (N=129) |
|
|---|---|
| URI5_NAP_1M_2M | |
| Mean (SD) | 0.0150 (1.00) |
| Median (IQR) | 0.0747 (1.26) |
| Missing | 25 (19.4%) |
| URI5_ACE | |
| Mean (SD) | -0.0574 (1.00) |
| Median (IQR) | -0.0912 (1.31) |
| Missing | 25 (19.4%) |
| URI5_FLU_PHE | |
| Mean (SD) | -0.0484 (1.00) |
| Median (IQR) | 0.0355 (1.32) |
| Missing | 25 (19.4%) |
| URI5_PYR | |
| Mean (SD) | -0.0201 (1.00) |
| Median (IQR) | 0.0727 (0.825) |
| Missing | 25 (19.4%) |
| URI5_CHR | |
| Mean (SD) | -0.0112 (1.00) |
| Median (IQR) | -0.0392 (0.957) |
| Missing | 25 (19.4%) |
Ambient exposures
| Overall (N=129) |
|
|---|---|
| bap_air | |
| Mean (SD) | 65.4 (86.9) |
| Median (IQR) | 39.4 (55.7) |
| Missing | 5 (3.9%) |
| pm25_air | |
| Mean (SD) | 197 (176) |
| Median (IQR) | 140 (132) |
| ANY_air | |
| Mean (SD) | 1040 (1790) |
| Median (IQR) | 552 (645) |
| Missing | 41 (31.8%) |
| BPE_air | |
| Mean (SD) | 70.6 (92.0) |
| Median (IQR) | 45.5 (53.1) |
| Missing | 5 (3.9%) |
| BaA_air | |
| Mean (SD) | 87.8 (145) |
| Median (IQR) | 40.5 (74.9) |
| Missing | 5 (3.9%) |
| BbF_air | |
| Mean (SD) | 106 (143) |
| Median (IQR) | 60.6 (89.3) |
| Missing | 5 (3.9%) |
| BkF_air | |
| Mean (SD) | 23.3 (31.7) |
| Median (IQR) | 13.4 (20.1) |
| Missing | 5 (3.9%) |
| CHR_air | |
| Mean (SD) | 83.3 (133) |
| Median (IQR) | 42.7 (73.6) |
| Missing | 5 (3.9%) |
| DBA_air | |
| Mean (SD) | 23.9 (35.9) |
| Median (IQR) | 12.7 (23.1) |
| Missing | 5 (3.9%) |
| FLT_air | |
| Mean (SD) | 59.6 (136) |
| Median (IQR) | 15.6 (37.9) |
| Missing | 5 (3.9%) |
| FLU_air | |
| Mean (SD) | 486 (680) |
| Median (IQR) | 273 (372) |
| Missing | 41 (31.8%) |
| IPY_air | |
| Mean (SD) | 43.0 (51.1) |
| Median (IQR) | 28.1 (34.8) |
| Missing | 5 (3.9%) |
| NAP_air | |
| Mean (SD) | 5730 (8740) |
| Median (IQR) | 3140 (3720) |
| Missing | 41 (31.8%) |
| PHE_air | |
| Mean (SD) | 730 (1050) |
| Median (IQR) | 388 (612) |
| Missing | 41 (31.8%) |
| PYR_air | |
| Mean (SD) | 66.2 (139) |
| Median (IQR) | 17.9 (49.0) |
| Missing | 5 (3.9%) |
Urinary biomarkers
| Overall (N=129) |
|
|---|---|
| Benzanthracene_Chrysene_urine | |
| Mean (SD) | 0.919 (3.17) |
| Median (IQR) | 0.384 (0.487) |
| Missing | 2 (1.6%) |
| Naphthalene_urine | |
| Mean (SD) | 224 (686) |
| Median (IQR) | 111 (111) |
| Methylnaphthalene_2_urine | |
| Mean (SD) | 45.8 (59.4) |
| Median (IQR) | 29.7 (30.6) |
| Missing | 9 (7.0%) |
| Methylnaphthalene_1_urine | |
| Mean (SD) | 19.7 (24.5) |
| Median (IQR) | 11.6 (18.1) |
| Missing | 4 (3.1%) |
| Acenaphthene_urine | |
| Mean (SD) | 7.40 (10.7) |
| Median (IQR) | 3.21 (5.57) |
| Phenanthrene_Anthracene_urine | |
| Mean (SD) | 204 (275) |
| Median (IQR) | 115 (194) |
| Fluoranthene_urine | |
| Mean (SD) | 21.0 (23.4) |
| Median (IQR) | 17.1 (17.3) |
| Pyrene_urine | |
| Mean (SD) | 0.715 (0.574) |
| Median (IQR) | 0.552 (0.411) |
| Missing | 18 (14.0%) |
1.2. Description of study population (first visit for all objects)
There are 129 visits with corresponding epigenetic ages available among 106 female subjects. For these 106 subjects, 83 have been visited once and 23 have been visited twice.
The following tables summarize all the information of the first visit of these 106 subjects.
Baseline characteristics (confounders)
| Overall (N=106) |
|
|---|---|
| Age | |
| Mean (SD) | 56.2 (15.0) |
| Median (IQR) | 58.0 (24.8) |
| BMI | |
| Mean (SD) | 22.0 (3.46) |
| Median (IQR) | 21.7 (4.46) |
| factor(county) | |
| Fuyuan | 53 (50.0%) |
| Xuanwe | 53 (50.0%) |
| factor(ses) | |
| 0 | 53 (50.0%) |
| 1 | 53 (50.0%) |
| factor(edu) | |
| 1 | 72 (67.9%) |
| 2 | 17 (16.0%) |
| 3 | 13 (12.3%) |
| 4 | 4 (3.8%) |
Epigenetic ages
| Overall (N=106) |
|
|---|---|
| DNAmAge | |
| Mean (SD) | 56.3 (13.5) |
| Median (IQR) | 57.6 (22.0) |
| DNAmAgeHannum | |
| Mean (SD) | 59.0 (14.4) |
| Median (IQR) | 59.9 (23.7) |
| DNAmPhenoAge | |
| Mean (SD) | 54.7 (14.0) |
| Median (IQR) | 54.8 (21.6) |
| DNAmAgeSkinBloodClock | |
| Mean (SD) | 55.8 (13.2) |
| Median (IQR) | 57.6 (23.5) |
| DNAmGrimAge | |
| Mean (SD) | 55.3 (11.8) |
| Median (IQR) | 57.2 (19.4) |
| DNAmTL | |
| Mean (SD) | 6.84 (0.329) |
| Median (IQR) | 6.85 (0.461) |
Epigenetic ages accelarations
| Overall (N=106) |
|
|---|---|
| AgeAccelerationResidual | |
| Mean (SD) | 0.182 (4.62) |
| Median (IQR) | 0.213 (5.90) |
| AgeAccelerationResidualHannum | |
| Mean (SD) | -0.435 (4.06) |
| Median (IQR) | -0.432 (4.79) |
| AgeAccelPheno | |
| Mean (SD) | -0.746 (4.45) |
| Median (IQR) | -1.06 (5.61) |
| DNAmAgeSkinBloodClockAdjAge | |
| Mean (SD) | -0.000985 (3.43) |
| Median (IQR) | 0.380 (3.58) |
| AgeAccelGrim | |
| Mean (SD) | -0.320 (2.96) |
| Median (IQR) | -0.913 (3.27) |
| DNAmTLAdjAge | |
| Mean (SD) | 0.0307 (0.182) |
| Median (IQR) | 0.0347 (0.238) |
| IEAA | |
| Mean (SD) | 0.0900 (4.34) |
| Median (IQR) | 0.303 (5.90) |
| EEAA | |
| Mean (SD) | -0.534 (5.24) |
| Median (IQR) | -0.425 (6.83) |
Fuel/stove type exposures
| Overall (N=106) |
|
|---|---|
| factor(curFuel) | |
| Smokeles | 13 (12.3%) |
| Smoky | 82 (77.4%) |
| Wood_and_or_Plant | 11 (10.4%) |
| factor(brthFuel) | |
| Mix | 43 (40.6%) |
| Outside of XW/FY | 3 (2.8%) |
| Smokeles | 5 (4.7%) |
| Smoky | 45 (42.5%) |
| Wood | 10 (9.4%) |
| factor(childFuel) | |
| Mix | 50 (47.2%) |
| Smokeles | 4 (3.8%) |
| Smoky | 43 (40.6%) |
| Wood | 9 (8.5%) |
| factor(curFuel_detail) | |
| Plant | 4 (3.8%) |
| Smokeles | 13 (12.3%) |
| Smoky | 82 (77.4%) |
| Wood | 7 (6.6%) |
| factor(cumFuel) | |
| Mix | 66 (62.3%) |
| Smokeles | 1 (0.9%) |
| Smoky | 37 (34.9%) |
| Wood | 2 (1.9%) |
| factor(curStove) | |
| Firepit_and_unventilated | 16 (15.1%) |
| Mix | 14 (13.2%) |
| Portable_stove | 16 (15.1%) |
| Ventilated | 44 (41.5%) |
| Missing | 16 (15.1%) |
5MC exposures
| Overall (N=106) |
|
|---|---|
| cur_5mc | |
| Mean (SD) | 8.13 (4.14) |
| Median (IQR) | 7.61 (4.48) |
| Missing | 2 (1.9%) |
| cum_5mc | |
| Mean (SD) | 266 (149) |
| Median (IQR) | 236 (194) |
| Missing | 2 (1.9%) |
| bir_5mc | |
| Mean (SD) | 5.14 (2.81) |
| Median (IQR) | 4.73 (5.23) |
| Missing | 2 (1.9%) |
| cur_5mc_measured | |
| Mean (SD) | 13.7 (40.7) |
| Median (IQR) | 5.71 (5.83) |
| Missing | 62 (58.5%) |
## [1] "Pearson pair-wise correlation:"## cur_5mc cum_5mc bir_5mc cur_5mc_measured
## cur_5mc 1.0000000 0.6947332 0.67276560 0.10959754
## cum_5mc 0.6947332 1.0000000 0.83239536 0.17329428
## bir_5mc 0.6727656 0.8323954 1.00000000 -0.05013945
## cur_5mc_measured 0.1095975 0.1732943 -0.05013945 1.00000000## [1] "Spearman pair-wise correlation:"## cur_5mc cum_5mc bir_5mc cur_5mc_measured
## cur_5mc 1.0000000 0.6291806 0.6239118 0.4534635
## cum_5mc 0.6291806 1.0000000 0.8206830 0.3159166
## bir_5mc 0.6239118 0.8206830 1.0000000 0.2008400
## cur_5mc_measured 0.4534635 0.3159166 0.2008400 1.0000000Cluster-based exposures
clusCUR6
Clusters based on model-based exposure estimates at or shortly before the visit
| Overall (N=106) |
|
|---|---|
| CUR6_BC_PAH6 | |
| Mean (SD) | 0.222 (0.975) |
| Median (IQR) | 0.799 (1.21) |
| Missing | 2 (1.9%) |
| CUR6_PAH31 | |
| Mean (SD) | 0.205 (0.977) |
| Median (IQR) | 0.433 (1.10) |
| Missing | 2 (1.9%) |
| CUR6_NkF | |
| Mean (SD) | -0.0581 (0.985) |
| Median (IQR) | -0.297 (1.20) |
| Missing | 2 (1.9%) |
| CUR6_PM_RET | |
| Mean (SD) | -0.0120 (1.01) |
| Median (IQR) | -0.298 (0.947) |
| Missing | 2 (1.9%) |
| CUR6_NO2 | |
| Mean (SD) | 0.0752 (1.00) |
| Median (IQR) | -0.0204 (1.14) |
| Missing | 2 (1.9%) |
| CUR6_SO2 | |
| Mean (SD) | -0.205 (0.995) |
| Median (IQR) | -0.335 (1.16) |
| Missing | 2 (1.9%) |
clusCHLD5
Clusters based on model-based exposure estimates accrued before age 18
| Overall (N=106) |
|
|---|---|
| CHLD5_X7 | |
| Mean (SD) | -0.0684 (0.965) |
| Median (IQR) | 0.0837 (0.991) |
| Missing | 2 (1.9%) |
| CHLD5_X33 | |
| Mean (SD) | 0.126 (0.995) |
| Median (IQR) | -0.0314 (1.65) |
| Missing | 2 (1.9%) |
| CHLD5_NkF | |
| Mean (SD) | -0.0960 (0.992) |
| Median (IQR) | -0.203 (1.36) |
| Missing | 2 (1.9%) |
| CHLD5_NO2 | |
| Mean (SD) | 0.119 (1.02) |
| Median (IQR) | 0.196 (1.18) |
| Missing | 2 (1.9%) |
| CHLD5_SO2 | |
| Mean (SD) | -0.0588 (1.00) |
| Median (IQR) | 0.355 (1.57) |
| Missing | 2 (1.9%) |
clusCUM6
Clusters based on model-based lifetime exposure estimates
| Overall (N=106) |
|
|---|---|
| CUM6_BC_NO2_PM | |
| Mean (SD) | 0.0305 (1.04) |
| Median (IQR) | 0.164 (1.71) |
| Missing | 2 (1.9%) |
| CUM6_PAH36 | |
| Mean (SD) | 0.141 (0.995) |
| Median (IQR) | 0.147 (1.65) |
| Missing | 2 (1.9%) |
| CUM6_DlP | |
| Mean (SD) | -0.196 (1.00) |
| Median (IQR) | -0.445 (1.70) |
| Missing | 2 (1.9%) |
| CUM6_NkF | |
| Mean (SD) | -0.0526 (1.02) |
| Median (IQR) | -0.150 (1.23) |
| Missing | 2 (1.9%) |
| CUM6_RET | |
| Mean (SD) | -0.156 (1.01) |
| Median (IQR) | -0.249 (1.12) |
| Missing | 2 (1.9%) |
| CUM6_SO2 | |
| Mean (SD) | -0.175 (1.00) |
| Median (IQR) | -0.0667 (1.62) |
| Missing | 2 (1.9%) |
clusMEAS6
Clusters based on pollutant measurements
| Overall (N=106) |
|
|---|---|
| MEAS6_BC_PM_RET | |
| Mean (SD) | 0.000103 (0.962) |
| Median [Min, Max] | 0.0484 [-2.12, 2.58] |
| Missing | 57 (53.8%) |
| MEAS6_X31 | |
| Mean (SD) | 0.0157 (0.910) |
| Median [Min, Max] | 0.148 [-1.94, 2.13] |
| Missing | 57 (53.8%) |
| MEAS6_X5 | |
| Mean (SD) | 0.00979 (0.975) |
| Median [Min, Max] | -0.102 [-1.42, 1.75] |
| Missing | 57 (53.8%) |
| MEAS6_DlP | |
| Mean (SD) | -0.0238 (0.992) |
| Median [Min, Max] | -0.640 [-1.02, 1.76] |
| Missing | 57 (53.8%) |
| MEAS6_NkF | |
| Mean (SD) | 0.0443 (1.02) |
| Median [Min, Max] | -0.489 [-1.18, 1.85] |
| Missing | 57 (53.8%) |
| MEAS6_NO2_SO2 | |
| Mean (SD) | 0.0300 (0.989) |
| Median [Min, Max] | -0.114 [-1.56, 2.06] |
| Missing | 57 (53.8%) |
clusURI5
Clusters based on urinary biomarkers
| Overall (N=106) |
|
|---|---|
| URI5_NAP_1M_2M | |
| Mean (SD) | 0.0130 (1.01) |
| Median (IQR) | 0.0739 (1.24) |
| Missing | 13 (12.3%) |
| URI5_ACE | |
| Mean (SD) | -0.118 (0.997) |
| Median (IQR) | -0.125 (1.35) |
| Missing | 13 (12.3%) |
| URI5_FLU_PHE | |
| Mean (SD) | -0.0444 (1.00) |
| Median (IQR) | 0.0608 (1.31) |
| Missing | 13 (12.3%) |
| URI5_PYR | |
| Mean (SD) | -0.0612 (1.03) |
| Median (IQR) | 0.0734 (0.925) |
| Missing | 13 (12.3%) |
| URI5_CHR | |
| Mean (SD) | -0.0236 (1.02) |
| Median (IQR) | -0.0342 (0.950) |
| Missing | 13 (12.3%) |
Ambient exposures
| Overall (N=106) |
|
|---|---|
| bap_air | |
| Mean (SD) | 66.3 (90.5) |
| Median (IQR) | 39.5 (55.9) |
| Missing | 3 (2.8%) |
| pm25_air | |
| Mean (SD) | 205 (188) |
| Median (IQR) | 144 (133) |
| ANY_air | |
| Mean (SD) | 908 (1540) |
| Median (IQR) | 486 (651) |
| Missing | 33 (31.1%) |
| BPE_air | |
| Mean (SD) | 69.2 (93.1) |
| Median (IQR) | 40.8 (51.7) |
| Missing | 3 (2.8%) |
| BaA_air | |
| Mean (SD) | 91.3 (153) |
| Median (IQR) | 43.7 (76.8) |
| Missing | 3 (2.8%) |
| BbF_air | |
| Mean (SD) | 110 (151) |
| Median (IQR) | 64.7 (92.2) |
| Missing | 3 (2.8%) |
| BkF_air | |
| Mean (SD) | 23.5 (33.2) |
| Median (IQR) | 13.2 (19.5) |
| Missing | 3 (2.8%) |
| CHR_air | |
| Mean (SD) | 88.0 (141) |
| Median (IQR) | 48.6 (74.5) |
| Missing | 3 (2.8%) |
| DBA_air | |
| Mean (SD) | 23.1 (35.9) |
| Median (IQR) | 11.0 (22.4) |
| Missing | 3 (2.8%) |
| FLT_air | |
| Mean (SD) | 65.2 (146) |
| Median (IQR) | 17.5 (41.0) |
| Missing | 3 (2.8%) |
| FLU_air | |
| Mean (SD) | 441 (691) |
| Median (IQR) | 250 (260) |
| Missing | 33 (31.1%) |
| IPY_air | |
| Mean (SD) | 40.9 (49.7) |
| Median (IQR) | 27.1 (33.5) |
| Missing | 3 (2.8%) |
| NAP_air | |
| Mean (SD) | 5340 (8070) |
| Median (IQR) | 3020 (3540) |
| Missing | 33 (31.1%) |
| PHE_air | |
| Mean (SD) | 675 (1080) |
| Median (IQR) | 351 (533) |
| Missing | 33 (31.1%) |
| PYR_air | |
| Mean (SD) | 71.3 (149) |
| Median (IQR) | 21.3 (50.6) |
| Missing | 3 (2.8%) |
Urinary biomarkers
| Overall (N=106) |
|
|---|---|
| Benzanthracene_Chrysene_urine | |
| Mean (SD) | 0.976 (3.49) |
| Median (IQR) | 0.389 (0.465) |
| Missing | 2 (1.9%) |
| Naphthalene_urine | |
| Mean (SD) | 247 (755) |
| Median (IQR) | 113 (112) |
| Methylnaphthalene_2_urine | |
| Mean (SD) | 48.7 (64.7) |
| Median (IQR) | 29.8 (29.4) |
| Missing | 8 (7.5%) |
| Methylnaphthalene_1_urine | |
| Mean (SD) | 21.0 (26.4) |
| Median (IQR) | 12.0 (18.7) |
| Missing | 3 (2.8%) |
| Acenaphthene_urine | |
| Mean (SD) | 7.76 (11.4) |
| Median (IQR) | 3.34 (5.84) |
| Phenanthrene_Anthracene_urine | |
| Mean (SD) | 216 (296) |
| Median (IQR) | 116 (191) |
| Fluoranthene_urine | |
| Mean (SD) | 21.8 (25.1) |
| Median (IQR) | 16.5 (17.5) |
| Pyrene_urine | |
| Mean (SD) | 0.744 (0.622) |
| Median (IQR) | 0.552 (0.423) |
| Missing | 15 (14.2%) |
1.3. EAA ~ confounders
## For AgeAccelerationResidual :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -0.2555 4.8412 -9.7443 9.2334 0.9579 > 0.05
## Age 0.0164 0.0416 -0.0651 0.0979 0.6940 > 0.05
## countyXuanwe -0.3183 0.8670 -2.0175 1.3810 0.7135 > 0.05
## BMI -0.0820 0.1092 -0.2961 0.1321 0.4528 > 0.05
## ses 1.9126 1.2040 -0.4472 4.2724 0.1122 > 0.05
## edu 0.4074 0.5870 -0.7431 1.5580 0.4876 > 0.05
## For AgeAccelerationResidualHannum :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -4.0613 4.1892 -12.2720 4.1495 0.3323 > 0.05
## Age 0.0447 0.0389 -0.0316 0.1209 0.2508 > 0.05
## countyXuanwe 0.4064 0.7888 -1.1396 1.9523 0.6064 > 0.05
## BMI 0.0047 0.0903 -0.1722 0.1817 0.9584 > 0.05
## ses -0.1213 1.2013 -2.4758 2.2332 0.9196 > 0.05
## edu 0.6429 0.5143 -0.3652 1.6509 0.2113 > 0.05
## For AgeAccelPheno :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -2.6519 3.9910 -10.4742 5.1704 0.5064 > 0.05
## Age 0.0252 0.0403 -0.0537 0.1042 0.5315 > 0.05
## countyXuanwe -0.4712 0.8431 -2.1237 1.1813 0.5763 > 0.05
## BMI 0.0553 0.0890 -0.1191 0.2298 0.5341 > 0.05
## ses -0.2758 1.0826 -2.3976 1.8461 0.7989 > 0.05
## edu -0.0725 0.5041 -1.0606 0.9155 0.8856 > 0.05
## For DNAmAgeSkinBloodClockAdjAge :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -1.5906 3.7271 -8.8957 5.7146 0.6696 > 0.05
## Age -0.0053 0.0399 -0.0835 0.0730 0.8954 > 0.05
## countyXuanwe -0.0470 0.6577 -1.3361 1.2421 0.9431 > 0.05
## BMI 0.0846 0.0778 -0.0678 0.2371 0.2766 > 0.05
## ses -0.2236 1.0918 -2.3634 1.9163 0.8377 > 0.05
## edu 0.1747 0.4783 -0.7627 1.1122 0.7149 > 0.05
## For AgeAccelGrim :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -1.0505 2.4045 -5.7633 3.6623 0.6622 > 0.05
## Age 0.0539 0.0234 0.0080 0.0998 0.0214 <= 0.05
## countyXuanwe -1.0738 0.5590 -2.1694 0.0218 0.0547 > 0.05
## BMI -0.1189 0.0652 -0.2468 0.0089 0.0683 > 0.05
## ses 1.7585 0.7244 0.3387 3.1784 0.0152 <= 0.05
## edu -0.0325 0.2801 -0.5815 0.5164 0.9076 > 0.05
## For DNAmTLAdjAge :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 0.2668 0.1305 0.0111 0.5226 0.0408 <= 0.05
## Age -0.0030 0.0014 -0.0057 -0.0003 0.0274 <= 0.05
## countyXuanwe 0.0277 0.0351 -0.0411 0.0965 0.4301 > 0.05
## BMI -0.0016 0.0041 -0.0095 0.0063 0.6937 > 0.05
## ses -0.0198 0.0493 -0.1165 0.0769 0.6879 > 0.05
## edu -0.0246 0.0152 -0.0545 0.0052 0.1056 > 0.05
## For IEAA :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 0.3629 4.8675 -9.1774 9.9031 0.9406 > 0.05
## Age 0.0186 0.0420 -0.0636 0.1009 0.6571 > 0.05
## countyXuanwe -0.6249 0.7946 -2.1824 0.9325 0.4316 > 0.05
## BMI -0.0702 0.1301 -0.3251 0.1848 0.5897 > 0.05
## ses 1.8296 1.2467 -0.6140 4.2732 0.1422 > 0.05
## edu -0.2049 0.5077 -1.2000 0.7902 0.6866 > 0.05
## For EEAA :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) -6.8361 5.1177 -16.8669 3.1947 0.1816 > 0.05
## Age 0.0710 0.0476 -0.0223 0.1643 0.1358 > 0.05
## countyXuanwe 0.6297 1.0042 -1.3387 2.5980 0.5307 > 0.05
## BMI 0.0083 0.1160 -0.2190 0.2357 0.9428 > 0.05
## ses 0.2458 1.4845 -2.6640 3.1555 0.8685 > 0.05
## edu 1.2008 0.6229 -0.0202 2.4218 0.0539 > 0.051.4. 5MC ~ confounders
## For cur_5mc :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 18.2037 4.7051 8.9817 27.4257 0.0001 <= 0.001
## Age -0.0869 0.0348 -0.1551 -0.0187 0.0125 <= 0.05
## countyXuanwe 0.7541 0.7996 -0.8132 2.3213 0.3457 > 0.05
## BMI -0.2026 0.1302 -0.4578 0.0526 0.1196 > 0.05
## ses -1.6191 1.1106 -3.7958 0.5576 0.1449 > 0.05
## edu -0.2050 0.4356 -1.0588 0.6488 0.6379 > 0.05
## For cum_5mc :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 205.6981 132.0974 -53.2128 464.6090 0.1194 > 0.05
## Age 3.1286 1.0698 1.0318 5.2254 0.0034 <= 0.01
## countyXuanwe 22.2370 26.7781 -30.2481 74.7222 0.4063 > 0.05
## BMI -3.7026 3.9015 -11.3496 3.9444 0.3426 > 0.05
## ses -30.6554 34.5139 -98.3026 36.9919 0.3744 > 0.05
## edu -20.3137 13.3902 -46.5585 5.9311 0.1293 > 0.05
## For bir_5mc :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 6.3683 1.9366 2.5726 10.1641 0.0010 <= 0.01
## Age -0.0053 0.0217 -0.0478 0.0372 0.8072 > 0.05
## countyXuanwe 0.3936 0.5482 -0.6809 1.4681 0.4728 > 0.05
## BMI -0.0093 0.0294 -0.0669 0.0483 0.7513 > 0.05
## ses -0.0277 0.7455 -1.4889 1.4334 0.9703 > 0.05
## edu -0.6050 0.2810 -1.1558 -0.0542 0.0313 <= 0.05
## For cur_5mc_measured :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 19.5262 28.7109 -36.7471 75.7995 0.4964 > 0.05
## Age 0.1232 0.2459 -0.3588 0.6052 0.6164 > 0.05
## countyXuanwe 16.2821 13.7250 -10.6188 43.1830 0.2355 > 0.05
## BMI -1.1442 1.1403 -3.3793 1.0908 0.3157 > 0.05
## ses -8.6827 11.4173 -31.0606 13.6951 0.4470 > 0.05
## edu 4.9116 6.0670 -6.9797 16.8029 0.4182 > 0.051.5. clusCUR6 ~ confounders
## For CUR6_BC_PAH6 :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 0.1239 0.8209 -1.4851 1.7329 0.8800 > 0.05
## Age 0.0057 0.0075 -0.0089 0.0204 0.4413 > 0.05
## countyXuanwe 0.6264 0.1812 0.2713 0.9816 0.0005 <= 0.001
## BMI -0.0186 0.0246 -0.0669 0.0296 0.4496 > 0.05
## ses 0.1084 0.2171 -0.3172 0.5340 0.6176 > 0.05
## edu -0.1224 0.1193 -0.3563 0.1116 0.3053 > 0.05
## For CUR6_PAH31 :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 2.1788 1.0617 0.0980 4.2597 0.0401 <= 0.05
## Age -0.0145 0.0086 -0.0313 0.0024 0.0920 > 0.05
## countyXuanwe 0.2369 0.1917 -0.1388 0.6125 0.2165 > 0.05
## BMI -0.0478 0.0301 -0.1068 0.0112 0.1121 > 0.05
## ses -0.2649 0.2421 -0.7394 0.2095 0.2738 > 0.05
## edu -0.0632 0.1196 -0.2976 0.1712 0.5973 > 0.05
## For CUR6_NkF :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 1.7328 0.9649 -0.1584 3.6240 0.0725 > 0.05
## Age -0.0143 0.0082 -0.0305 0.0018 0.0817 > 0.05
## countyXuanwe -0.1208 0.1900 -0.4933 0.2516 0.5249 > 0.05
## BMI -0.0414 0.0303 -0.1009 0.0180 0.1720 > 0.05
## ses -0.1386 0.2636 -0.6554 0.3781 0.5990 > 0.05
## edu 0.0387 0.1199 -0.1963 0.2736 0.7469 > 0.05
## For CUR6_PM_RET :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 1.1110 0.8437 -0.5428 2.7647 0.1879 > 0.05
## Age -0.0027 0.0108 -0.0239 0.0184 0.8016 > 0.05
## countyXuanwe -0.3576 0.1966 -0.7430 0.0278 0.0689 > 0.05
## BMI -0.0303 0.0208 -0.0711 0.0105 0.1450 > 0.05
## ses -0.0712 0.3003 -0.6599 0.5174 0.8125 > 0.05
## edu -0.0575 0.0978 -0.2492 0.1343 0.5567 > 0.05
## For CUR6_NO2 :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 0.5882 0.8110 -1.0014 2.1777 0.4683 > 0.05
## Age 0.0010 0.0077 -0.0141 0.0160 0.8997 > 0.05
## countyXuanwe -0.7780 0.1836 -1.1379 -0.4181 0.0000 <= 0.001
## BMI 0.0004 0.0230 -0.0447 0.0454 0.9866 > 0.05
## ses -0.2574 0.2255 -0.6994 0.1845 0.2536 > 0.05
## edu -0.0300 0.1405 -0.3054 0.2453 0.8307 > 0.05
## For CUR6_SO2 :[1] "Fitting with 129 observations."
## coefficient std ci_lower ci_upper p_val sig_level
## (Intercept) 0.5267 0.8807 -1.1996 2.2529 0.5499 > 0.05
## Age -0.0080 0.0102 -0.0281 0.0120 0.4308 > 0.05
## countyXuanwe -0.4910 0.1868 -0.8571 -0.1248 0.0086 <= 0.01
## BMI 0.0037 0.0109 -0.0177 0.0251 0.7365 > 0.05
## ses -0.3921 0.2544 -0.8906 0.1065 0.1232 > 0.05
## edu 0.0577 0.1441 -0.2247 0.3401 0.6890 > 0.05Fuel Types Summary table
Current Fuel vs Birth Fuel + Cumulative
## brthFuel cumFuel Smokeles Smoky Wood_and_or_Plant
## 1 Mix Mix 9 38 7
## 2 Outside of XW/FY Mix 1 2 0
## 3 Smokeles Mix 2 4 0
## 4 Smokeles Smokeles 0 1 0
## 5 Smoky Mix 3 7 0
## 6 Smoky Smoky 1 41 0
## 7 Wood Mix 2 5 4
## 8 Wood Wood 0 0 22. PCA
3. Explore clocks
3.1. Clock values
3.2. Correlogram
Between clocks
All visits included
3.3. Median absolute error
## DNAmAge DNAmAgeHannum DNAmPhenoAge
## 3.455101 3.380488 3.005900
## DNAmAgeSkinBloodClock DNAmGrimAge
## 2.585191 4.0637203.4. Scatterplots of age vs each epigenetic age
4. Explore Exposure Measurements
4.1. Correlogram
4.1.1. Between Ambient Exposure Measurements
4.1.2. Between Urinary Exposure Measurements
4.1.3. Between Ambient and Urinary Exposure Measurements
4.1.4. Between Clustered Exposure Measurements
